code: def test_inference_no_head_absolute_embedding(self):
      model = FlaxAlbertModel.from_pretrained("albert-base-v2")
      input_ids = np.array(
          [[0, 345, 232, 328, 740, 140, 1695, 69, 6078, 1588, 2]]
      )
      attention_mask = np.array([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]])
      output = model(input_ids, attention_mask=attention_mask)[0]
      expected_shape = (1, 11, 768)
      self.assertEqual(output.shape, expected_shape)
      expected_slice = np.array(
          [
              [
                  [-0.6513, 1.5035, -0.2766],
                  [-0.6515, 1.5046, -0.2780],
                  [-0.6512, 1.5049, -0.2784],
              ]
          ]
      )
  
      self.assertTrue(
          jnp.allclose(output[:, 1:4, 1:4], expected_slice, atol=1e-4)
      )
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/tests/models/albert/test_modeling_flax_albert.py
imports: import unittest
  import numpy
  from transformers import AlbertConfig, is_flax_available
  from transformers.testing_utils import require_flax, slow
  from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
label_desc: Use image node_id 1 for calling the FlaxAlbertModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_no_head_absolute_embedding() without return types